Abstract

We consider autonomous agents communicating over a random communication network that is subject to failures. Each agent aims to maximize its own utility function that depends on the actions of other agents and an unknown state of the environment. Posing this problem as a game, we study a decentralized fictitious play algorithm with a voluntary communication protocol (DFP-V) for Nash equilibrium (NE) computation. In the voluntary communication protocol, each agent locally manages whom to exchange information with by assessing the novelty of its information and the potential effect of its information on others' assessments of their utility functions. We show convergence of the algorithm to a pure NE in finite time for the class of weakly acyclic games. Numerical experiments demonstrate that the voluntary communication protocol reduces number of communication attempts significantly without hampering performance.

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